Conclusions

In the past decade, I’ve seen a growing awareness about systems and complexity thinking and the development of “user-friendly” systems science tools. But I’ve also noticed a strong bias toward the reductionist science tools as “real” or rigorous science. Although many people in healthcare are now recognizing systems science concepts, they tend to treat it as a soft science, not as valuable or valid as a rigorous prospective RCTs. However, the systems science paradigm provides a much more complete description of how our world really functions and so the tools are much more valuable to apply for true learning and improvement in healthcare.
The tools of systems science such as CQI, non-linear analytics and team-based patient care coordination and management have the potential to focus on the goal of improving the value of care for our patients. That also will improve the value for all the parts of our system that contribute to that value and reduce harm and waste. This will take effort at the level of each local environment and in the context of each definable patient care process.
We are going through a paradigm shift in the scientific understanding of our world, from the machine as a metaphor for human beings to an understanding that we are complex, adaptive and dynamic systems – imperfect and nonlinear, but able to adapt in many various ways. We can’t change the fact that the pace of change and complexity in our world, like the expansion of our universe, is increasing at an accelerating rate. But we can learn to apply the science of systems so that we can learn to improve the value care for patients and our system-as-a-whole. This will allow us to transform our global healthcare system to one that is sustainable, and I believe this can lead to a better world.
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